Dataconomy

MARCH 20, 2025

These APIs simplify user interactions and expedite the development of data pipelines. in early 2017. High-level APIs Google encourages the use of high-level APIs, such as Keras, for building machine learning models. Released as open-source in 2015 under the Apache 2.0

Machine Learning 91

Machine Learning Machine Learning Deep Learning Deep Learning 91

DataRobot Blog

OCTOBER 3, 2017

“Having information in one place – from first-party data, to second- and third-party data – has made every additional use case an incremental add-on,” he said, emphasizing that being modular helped them to avoid creating data pipelines for every use case. “We 3) Data professionals come in all shapes and forms.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

AWS Machine Learning Blog

DECEMBER 4, 2024

Through simple conversations, business teams can use the chat agent to extract valuable insights from both structured and unstructured data sources without writing code or managing complex data pipelines. The structured dataset includes order information for products spanning from 2010 to 2017.

AWS 106

AWS AI AI SQL 106

DataRobot Blog

APRIL 1, 2018

In Nick Heudecker’s session on Driving Analytics Success with Data Engineering , we learned about the rise of the data engineer role – a jack-of-all-trades data maverick who resides either in the line of business or IT. 3) The emergence of a new enterprise information management platform. Sallam | Cindi Howson | Carlie J.

Analytics 40

Analytics Analytics Data Preparation Augmented Analytics 40

DagsHub

DECEMBER 11, 2023

It does not support the ‘dvc repro’ command to reproduce its data pipeline. DVC Released in 2017, Data Version Control ( DVC for short) is an open-source tool created by iterative. DagsHub calculates the new hashes, and commit the new DVC-tracked and modified Git-tracked files on the users’ behalf.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

Flipboard

NOVEMBER 24, 2023

The humble beginnings with Iris In 2017, SnapLogic unveiled Iris, an industry-first AI-powered integration assistant. Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline.

Database 155

Database AWS ETL SQL 155

The MLOps Blog

DECEMBER 28, 2022

Organization Acquia Industry Software-as-a-service Team size Acquia built an ML team five years ago in 2017 and has a team size of 6. Team composition The team comprises data pipeline engineers, ML engineers, full-stack engineers, and data scientists.

ML 78

ML ML Data Scientist Machine Learning 78